I’m writing this from Shanghai where I’m a Visiting Professor. I watched a fascinating show on the use of Big Data to understand why some of the companies have rebounded from the Fukiyama Nuclear disaster and others haven’t. For those of you (who like me are) interested in big data, see the video produced by NHK World.
One element was not about analyzing the data on patterns with phone calls, twitters, computer connections, etc. but on Opinion Leadership. After the disaster, many people stopped eating food grown in the area. The question was what would determine when people would encourage others to return to eating the fruit because it was now being grown in healthy soil. The specific question involved peaches.
To get to the answer, they monitored tweets by opinion leaders – defined as people who were providing tweets that were re-tweeted. (FYI: I’ve been interested in opinion leadership and the adoption of innovations (or changes) since I studied it and used it as one of the bases for my Ph.D. dissertation on patterns of birth control use by teenage women.) What they discovered is that the number of re-tweets for positive and negative information was about the same. But the sources were different! Positive comments (e.g., healthy peaches were now available and good to eat) was tweeted by one person and then re-tweeted several times by other people. In contrast, negative comments (e.g., I would never eat any peaches grown near Fukiyama) were tweeted by a person and then re-tweeted with additional comments several times by the same person. So analysis of re-tweets requires that you study the sources!
They actually traced one negative tweeter who after 2 years began tweeting positive comments. She admitted to having really negative opinions and wanted to share them actively, hence re-tweeting her own information. Then she had the chance to visit a farm and learned about the steps taken to make the food healthy. She tasted the peaches and loved them. She then began tweeting about her new perspective – and the retweets of her comments followed the traditional pattern. After making a few positive comments – other people’s re-tweets, rather than her own accounted for the new retreats.
As you can see, how we influence people is different, and even big data may allow us to tap more effectively into this process.  Share your experiences with re-tweets, opinion leadership and big data!